fix imports

Author: Enias Cailliau

build/archives/gymbro-bot_v0.3.0-rc.21.zip

@@ -1,16 +1,15 @@
 import logging
 import sys
+
+sys.path.insert(0, "src")
 from functools import partial
 from typing import List
 
 from steamship.experimental.transports.chat import ChatMessage
-
-from api import LangChainTelegramChatbot
-
-sys.path.insert(0, "src")
 from steamship import Steamship, SteamshipError
 from steamship.cli.ship_spinner import ship_spinner
 from termcolor import colored
+from api import LangChainTelegramChatbot
 
 
 def show_results(response_messages: List[ChatMessage]):
@@ -36,7 +35,10 @@ def main():
     Steamship()
 
     with Steamship.temporary_workspace() as client:
-        run = partial(run_agent, agent=LangChainTelegramChatbot(client=client, config={"bot_token": "test"}))
+        run = partial(
+            run_agent,
+            agent=LangChainTelegramChatbot(client=client, config={"bot_token": "test"}),
+        )
         print(f"Starting Agent...")
 
         print(
@@ -60,9 +62,13 @@ def run_agent(agent, prompt: str, as_api: bool = False) -> None:
     if not agent.is_verbose_logging_enabled():  # display progress when verbose is False
         print("Running: ", end="")
         with ship_spinner():
-            response = agent.create_response(incoming_message=ChatMessage(text=prompt, chat_id="123"))
+            response = agent.create_response(
+                incoming_message=ChatMessage(text=prompt, chat_id="123")
+            )
     else:
-        response = agent.create_response(incoming_message=ChatMessage(text=prompt, chat_id="123"))
+        response = agent.create_response(
+            incoming_message=ChatMessage(text=prompt, chat_id="123")
+        )
 
     show_results(response)
 

main.py

@@ -13,7 +13,6 @@
 
 
 class LangChainAgentBot(TelegramBot):
-
     @abstractmethod
     def get_agent(self, chat_id: str) -> AgentExecutor:
         raise NotImplementedError()
@@ -40,7 +39,7 @@ def _invoke_later(self, delay_ms: int, message: str, chat_id: str):
         )
 
     def create_response(
-            self, incoming_message: ChatMessage
+        self, incoming_message: ChatMessage
     ) -> Optional[List[ChatMessage]]:
         """Use the LLM to prepare the next response by appending the user input to the file and then generating."""
         if incoming_message.text == "/start":
@@ -62,7 +61,7 @@ def create_response(
         )
 
     def agent_output_to_chat_messages(
-            self, chat_id: str, agent_output: List[str]
+        self, chat_id: str, agent_output: List[str]
     ) -> List[ChatMessage]:
         """Transform the output of the Multi-Modal Agent into a list of ChatMessage objects.
 

src/__pycache__/api.cpython-38.pyc

@@ -31,33 +31,34 @@ class LangChainTelegramChatbot(LangChainAgentBot):
     """Deploy LangChain chatbots and connect them to Telegram."""
 
     def get_agent(self, chat_id: str) -> AgentExecutor:
-        llm = OpenAIChat(client=self.client,
-                         temperature=TEMPERATURE,
-                         verbose=True)
+        llm = OpenAIChat(client=self.client, temperature=TEMPERATURE, verbose=True)
 
         tools = self.get_tools(chat_id=chat_id)
 
         my_instance_handle = "local-also-remind-me-will-not-work"
 
-        memory = ConversationBufferMemory(memory_key="chat_history",
-                                          chat_memory=ChatMessageHistory(
-                                              client=self.client,
-                                              key=f"history-{chat_id}-{my_instance_handle}"
-                                          ),
-                                          return_messages=True)
+        memory = ConversationBufferMemory(
+            memory_key="chat_history",
+            chat_memory=ChatMessageHistory(
+                client=self.client, key=f"history-{chat_id}-{my_instance_handle}"
+            ),
+            return_messages=True,
+        )
 
-        return initialize_agent(tools,
-                                llm,
-                                agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION,
-                                verbose=True,
-                                # agent_kwargs={"output_parser":MultiModalParser()},
-                                memory=memory)
+        return initialize_agent(
+            tools,
+            llm,
+            agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION,
+            verbose=True,
+            # agent_kwargs={"output_parser":MultiModalParser()},
+            memory=memory,
+        )
 
     def get_tools(self, chat_id: str) -> List[Tool]:
         return [
             SearchTool(self.client),
             # MyTool(self.client),
             GenerateImageTool(self.client),
             # GenerateAlbumArtTool(self.client)
-            RemindMe(invoke_later=self.invoke_later, chat_id=chat_id)
+            RemindMe(invoke_later=self.invoke_later, chat_id=chat_id),
         ]

src/agent/__pycache__/__init__.cpython-38.pyc

@@ -1,7 +1,7 @@
 {
 	"type": "package",
 	"handle": "gymbro-bot",
-	"version": "0.3.0-rc.19",
+	"version": "0.3.0-rc.21",
 	"description": "Deploy your LangChain chatbots to Telegram.",
 	"author": "",
 	"entrypoint": "Unused",